Volume 20, Issue 5 (2020)                   MCEJ 2020, 20(5): 131-141 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Zialame A, Jamshidi A, Khodadadi A. Optimization of Arsenic Adsorption from Solution Using Nano-Jacobsite by Response Surface Method (RSM). MCEJ 2020; 20 (5) :131-141
URL: http://mcej.modares.ac.ir/article-16-35459-en.html
1- Master of mining engineering, Mining and Envirronment, Tarbiat Modares University.
2- 2- Faculty of Engineering, Department of Mining, Tarbiat Modares University. , ajamshidi@modares.ac.ir
3- Professor of mineral proceessing, Tarbiat Modares University.
Abstract:   (1311 Views)
Lots of ecosystems including soil and water in the world is contaminated by the arsenic every year. The emission of arsenic (As) to the surface and groundwater by human activities such as mining, agricultural and industrial activities is considered a global threat to the ecosystem and human health. Arsenite and arsenate are the two dominant arsenic species in contaminated soils that are highly toxic to the human health and ecosystems. Thus, the As elimination from aqueous solution is considered as crucial issue. Among the different removal methods, adsorption is the low cost, and high efficient technique for the As elimination from aqueous phase. In the adsorption process, the adsorbent type is the one of the main factors of successful removal process. Application of nano-adsrobent may lead to produce less secondary waste in the adsorption process. Moreover, bimetal nano-adsorbent due to the some properties including increasing As removal in the early time was selected as adsorbent to remove As from aqueous solution. Many researches believe that Jacobsite nanoparticles (MnFe2O4) are an effective absorbent for the removal of organic and inorganic materials. Due to the special properties of nanoparticles such as high reactivity, Jacobsite nanoparticles were selected for the adsorption of arsenic from water and prepared based on co-precipitation method. The prepared nanoparticles were characterized through the X-ray fluorescence (XRF), X-ray diffraction XRD, scanning electron microscopy methods (SEM), and pHpzc. According to the XRD, the obtained peaks for the synthesized adsorbent were followed by the previous researches indicated the production of Jacobsite. Based on the XRF, the Mn-oxide and Fe-oxide was 27.8% and 65.5%, respectively. Overall, results of XRD and XRF proved that the synthesized nanoparticles were Jacobsite. Moreover, based on the Fe-SEM, the nanoparticle size was less than 100 nm with mean size of 33.8 nm. Moreover, the he pH of zero point of the nanoparticle (pHpzc) of the synthesized adsorbent was 7.2.  In the presnet study, Response Surface Methodology (RSM) was used to model and optimize the adsorption process of arsenic from solution with Jacobsite nanoparticles. Four factors of pH (3 to 11), concentration of arsenic in solution (1000 to 4000 μg/l), amount of nanoparticles (1 to 5 g/l) and time (15 to 195 min) were selected as independent factors affecting the adsorption efficiency of arsenic. The central composite design (CCD) was used to design of the experiment and optimize the model parameters. Variance analysis indicated that prediction of adsorption of arsenic from the nano-adsorbent by the CCD model was well performed (p <0.0001) with the high accuracy (R2 of 96.24%). The results showed that the effect of four factors pH, nanoparticles, initial arsenic concentration and time was significant. According to the optimization objectives, the results showed that the optimum pH, amount of nanoparticles, time and initial concentration of arsenic were 3, 2 g / l, 48 min and 3250 μg/l, respectively. The arsenic removal from the solution at optimum values ​​calculated for the factors was estimated to be 79.7%. However, 94.77% of As was removed in the adsorption experiments.
Full-Text [PDF 1013 kb]   (547 Downloads)    
Article Type: Original Research | Subject: Environment
Received: 2019/08/5 | Accepted: 2020/01/18 | Published: 2020/11/30

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.